File operations in a distributed storage system

ABSTRACT

A plurality of computing devices are communicatively coupled to each other via a network, and each of the plurality of computing devices is operably coupled to one or more of a plurality of storage devices. A plurality of failure resilient address spaces are distributed across the plurality of storage devices such that each of the plurality of failure resilient address spaces spans a plurality of the storage devices. The plurality of computing devices maintains metadata that maps each failure resilient address space to one of the plurality of computing devices. Each of the plurality of computing devices is operable to read from and write to a plurality of memory blocks, while maintaining an extent in metadata that maps the plurality of memory blocks to the failure resilient address space.

PRIORITY CLAIM

This application is a continuation of United States patent application16/121,508, filed Sep. 4, 2018, which claims priority to United Statesprovisional patent application 62/585,057 titled “File Operations In ADistributed Storage System” filed on Nov. 13, 2017, now expired. Each ofthe aforementioned documents are incorporated herein by reference intheir entirety.

INCORPORATION BY REFERENCE

U.S. patent application Ser. No. 15/243,519 titled “Distributed ErasureCoded Virtual File System” is hereby incorporated herein by reference inits entirety.

BACKGROUND

Limitations and disadvantages of conventional approaches to data storagewill become apparent to one of skill in the art, through comparison ofsuch approaches with some aspects of the present method and system setforth in the remainder of this disclosure with reference to thedrawings.

BRIEF SUMMARY

Methods and systems are provided for file operations in a distributedstorage system substantially as illustrated by and/or described inconnection with at least one of the figures, as set forth morecompletely in the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates various example configurations of a virtual filesystem in accordance with aspects of this disclosure.

FIG. 2 illustrates an example configuration of a virtual file systemnode in accordance with aspects of this disclosure.

FIG. 3 illustrates another representation of a virtual file system inaccordance with an example implementation of this disclosure.

FIG. 4 illustrates an example of a flash registry with write leveling inaccordance with an example implementation of this disclosure.

FIG. 5 illustrates an example of a shadow registry associated with theflash registry in FIG. 4 in accordance with an example implementation ofthis disclosure.

DETAILED DESCRIPTION

The systems in this disclosure are applicable to small clusters and canalso scale to many, many thousands of nodes. An example embodiment isdiscussed regarding non-volatile memory (NVM), for example, flash memorythat comes in the form of a solid-state drive (SSD). The NVM may bedivided into 4 kB “blocks” and 128 MB “chunks.” “Extents” may be storedin volatile memory, e.g., RAM for fast access, backed up by NVM storageas well. An extent may store pointers for blocks, e.g., 256 pointers to1 MB of data stored in blocks. In other embodiments, larger or smallermemory divisions may also be used. Metadata functionality in thisdisclosure may be effectively spread across many servers. For example,in cases of “hot spots” where a large load is targeted at a specificportion of the filesystem's namespace, this load can be distributedacross a plurality of nodes.

FIG. 1 illustrates various example configurations of a virtual filesystem (VFS) in accordance with aspects of this disclosure. Shown inFIG. 1 is a local area network (LAN) 102 comprising one or more VFSnodes 120 (indexed by integers from 1 to J, for j≥1), and optionallycomprising (indicated by dashed lines): one or more dedicated storagenodes 106 (indexed by integers from 1 to M, for M≥1), one or morecompute nodes 104 (indexed by integers from 1 to N, for N≥1), and/or anedge router that connects the LAN 102 to a remote network 118. Theremote network 118 optionally comprises one or more storage services 114(indexed by integers from 1 to K, for K≥1), and/or one or more dedicatedstorage nodes 115 (indexed by integers from 1 to L, for L≥1).

Each VFS node 120 _(j) (j an integer, where 1≤j≤J) is a networkedcomputing device (e.g., a server, personal computer, or the like) thatcomprises circuitry for running VFS processes and, optionally, clientprocesses (either directly on an operating system of the device 104 _(n)and/or in one or more virtual machines running in the device 104 _(n)).

The compute nodes 104 are networked devices that may run a VFS frontendwithout a VFS backend. A compute node 104 may run VFS frontend by takingan SR-IOV into the NIC and consuming a complete processor core.Alternatively, the compute node 104 may run the VFS frontend by routingthe networking through a Linux kernel networking stack and using kernelprocess scheduling, thus not having the requirement of a full core. Thisis useful if a user does not want to allocate a complete core for theVFS or if the networking hardware is incompatible with the VFSrequirements.

FIG. 2 illustrates an example configuration of a VFS node in accordancewith aspects of this disclosure. A VFS node comprises a VFS frontend 202and driver 208, a VFS memory controller 204, a VFS backend 206, and aVFS SSD agent 214. As used in this disclosure, a “VFS process” is aprocess that implements one or more of: the VFS frontend 202, the VFSmemory controller 204, the VFS backend 206, and the VFS SSD agent 214.Thus, in an example implementation, resources (e.g., processing andmemory resources) of the VFS node may be shared among client processesand VFS processes. The processes of the VFS may be configured to demandrelatively small amounts of the resources to minimize the impact on theperformance of the client applications. The VFS frontend 202, the VFSmemory controller 204, and/or the VFS backend 206 and/or the VFS SSDagent 214 may run on a processor of the host 201 or on a processor ofthe network adaptor 218. For a multi-core processor, different VFSprocess may run on different cores, and may run a different subset ofthe services. From the perspective of the client process(es) 212, theinterface with the virtual file system is independent of the particularphysical machine(s) on which the VFS process(es) are running. Clientprocesses only require driver 208 and frontend 202 to be present inorder to serve them.

The VFS node may be implemented as a single tenant server (e.g.,bare-metal) running directly on an operating system or as a virtualmachine (VM) and/or container (e.g., a Linux container (LXC)) within abare-metal server. The VFS may run within an LXC container as a VMenvironment. Thus, inside the VM, the only thing that may run is the LXCcontainer comprising the VFS. In a classic bare-metal environment, thereare user-space applications and the VFS runs in an LXC container. If theserver is running other containerized applications, the VFS may runinside an LXC container that is outside the management scope of thecontainer deployment environment (e.g. Docker).

The VFS node may be serviced by an operating system and/or a virtualmachine monitor (VMM) (e.g., a hypervisor). The VMM may be used tocreate and run the VFS node on a host 201. Multiple cores may resideinside the single LXC container running the VFS, and the VFS may run ona single host 201 using a single Linux kernel. Therefore, a single host201 may comprise multiple VFS frontends 202, multiple VFS memorycontrollers 204, multiple VFS backends 206, and/or one or more VFSdrivers 208. A VFS driver 208 may run in kernel space outside the scopeof the LXC container.

A single root input/output virtualization (SR-IOV) PCIe virtual functionmay be used to run the networking stack 210 in user space 222. SR-IOVallows the isolation of PCI Express, such that a single physical PCIExpress can be shared on a virtual environment and different virtualfunctions may be offered to different virtual components on a singlephysical server machine. The I/O stack 210 enables the VFS node tobypasses the standard TCP/IP stack 220 and communicate directly with thenetwork adapter 218. A Portable Operating System Interface for uniX(POSIX) VFS functionality may be provided through lockless queues to theVFS driver 208. SR-IOV or full PCIe physical function address may alsobe used to run non-volatile memory express (NVMe) driver 214 in userspace 222, thus bypassing the Linux IO stack completely. NVMe may beused to access non-volatile storage media 216 attached via a PCI Express(PCIe) bus. The non-volatile storage media 220 may be, for example,flash memory that comes in the form of a solid-state drive (SSD) orStorage Class Memory (SCM) that may come in the form of an SSD or amemory module (DIMM). Other example may include storage class memorytechnologies such as 3D-XPoint.

The SSD may be implemented as a networked device by coupling thephysical SSD 216 with the SSD agent 214 and networking 210.Alternatively, the SSD may be implemented as a network-attached NVMe SSD222 or 224 by using a network protocol such as NVMe-oF (NVMe overFabrics). NVMe-oF may allow access to the NVMe device using redundantnetwork links, thereby providing a higher level or resiliency. Networkadapters 226, 228, 230 and 232 may comprise hardware acceleration forconnection to the NVMe SSD 222 and 224 to transform them into networkedNVMe-oF devices without the use of a server. The NVMe SSDs 222 and 224may each comprise two physical ports, and all the data may be accessedthrough either of these ports.

Each client process/application 212 may run directly on an operatingsystem or may run in a virtual machine and/or container serviced by theoperating system and/or hypervisor. A client process 212 may read datafrom storage and/or write data to storage in the course of performingits primary function. The primary function of a client process 212,however, is not storage-related (i.e., the process is only concernedthat its data is reliably stored and is retrievable when needed, and notconcerned with where, when, or how the data is stored). Exampleapplications which give rise to such processes include: email servers,web servers, office productivity applications, customer relationshipmanagement (CRM), animated video rendering, genomics calculation, chipdesign, software builds, and enterprise resource planning (ERP).

A client application 212 may make a system call to the kernel 224 whichcommunicates with the VFS driver 208. The VFS driver 208 puts acorresponding request on a queue of the VFS frontend 202. If several VFSfrontends exist, the driver may load balance accesses to the differentfrontends, making sure a single file/directory is always accessed viathe same frontend. This may be done by “sharding” the frontend based onthe ID of the file or directory. The VFS frontend 202 provides aninterface for routing file system requests to an appropriate VFS backendbased on the bucket that is responsible for that operation. Theappropriate VFS backend may be on the same host or it may be on anotherhost.

The VFS backend 206 hosts several buckets, each one of them services thefile system requests that it receives and carries out tasks to otherwisemanage the virtual file system (e.g., load balancing, journaling,maintaining metadata, caching, moving of data between tiers, removingstale data, correcting corrupted data, etc.)

The VFS SSD agent 214 handles interactions with a respective storagedevice 216. This may include, for example, translating addresses, andgenerating the commands that are issued to the storage device (e.g., ona SATA, SAS, PCIe, or other suitable bus). Thus, the VFS SSD agent 214operates as an intermediary between a storage device 216 and the VFSbackend 206 of the virtual file system. The SSD agent 214 could alsocommunicate with a standard network storage device supporting a standardprotocol such as NVMe-oF (NVMe over Fabrics).

FIG. 3 illustrates another representation of a virtual file system inaccordance with an example implementation of this disclosure. In FIG. 3, the element 302 represents memory resources (e.g., DRAM and/or othershort-term memory) and processing (e.g., x86 processor(s), ARMprocessor(s), NICs, ASICs, FPGAs, and/or the like) resources of variousnode(s) (compute, storage, and/or VFS) on which resides a virtual filesystem, such as described regarding FIG. 2 above. The element 308represents the one or more physical storage devices 216 which providethe long term storage of the virtual file system.

As shown in FIG. 3 , the physical storage is organized into a pluralityof distributed failure resilient address spaces (DFRASs) 518. Each ofwhich comprises a plurality of chunks 310, which in turn comprises aplurality of blocks 312. The organization of blocks 312 into chunks 310is only a convenience in some implementations and may not be done in allimplementations. Each block 312 stores committed data 316 (which maytake on various states, discussed below) and/or metadata 314 thatdescribes or references committed data 316.

The organization of the storage 308 into a plurality of DFRASs enableshigh performance parallel commits from many—perhaps all—of the nodes ofthe virtual file system (e.g., all nodes 104 ₁-104 _(N), 106 ₁-106 _(M),and 120 ₁-120 _(J) of FIG. 1 may perform concurrent commits inparallel). In an example implementation, each of the nodes of thevirtual file system may own a respective one or more of the plurality ofDFRAS and have exclusive read/commit access to the DFRASs that it owns.

Each bucket owns a DFRAS, and thus does not need to coordinate with anyother node when writing to it. Each bucket may build stripes across manydifferent chunks on many different SSDs, thus each bucket with its DFRAScan choose what “chunk stripe” to write to currently based on manyparameters, and there is no coordination required in order to do so oncethe chunks are allocated to that bucket. All buckets can effectivelywrite to all SSDs without any need to coordinate.

Each DFRAS being owned and accessible by only its owner bucket that runson a specific node allows each of the nodes of the VFS to control aportion of the storage 308 without having to coordinate with any othernodes (except during [re]assignment of the buckets holding the DFRASsduring initialization or after a node failure, for example, which may beperformed asynchronously to actual reads/commits to storage 308). Thus,in such an implementation, each node may read/commit to its buckets'DFRASs independently of what the other nodes are doing, with norequirement to reach any consensus when reading and committing tostorage 308. Furthermore, in the event of a failure of a particularnode, the fact the particular node owns a plurality of buckets permitsmore intelligent and efficient redistribution of its workload to othernodes (rather the whole workload having to be assigned to a single node,which may create a “hot spot”). In this regard, in some implementationsthe number of buckets may be large relative to the number of nodes inthe system such that any one bucket may be a relatively small load toplace on another node. This permits fine grained redistribution of theload of a failed node according to the capabilities and capacity of theother nodes (e.g., nodes with more capabilities and capacity may begiven a higher percentage of the failed nodes buckets).

To permit such operation, metadata may be maintained that maps eachbucket to its current owning node such that reads and commits to storage308 can be redirected to the appropriate node.

Load distribution is possible because the entire filesystem metadataspace (e.g., directory, file attributes, content range in the file,etc.) can be broken (e.g., chopped or sharded) into small, uniformpieces (e.g., “shards”). For example, a large system with 30k serverscould chop the metadata space into 128k or 256k shards.

Each such metadata shard may be maintained in a “bucket.” Each VFS nodemay have responsibility over several buckets. When a bucket is servingmetadata shards on a given backend, the bucket is considered “active” orthe “leader” of that bucket. Typically, there are many more buckets thanVFS nodes. For example, a small system with 6 nodes could have 120buckets, and a larger system with 1,000 nodes could have 8k buckets.

Each bucket may be active on a small set of nodes, typically 5 nodesthat that form a penta-group for that bucket. The cluster configurationkeeps all participating nodes up-to-date regarding the penta-groupassignment for each bucket.

Each penta-group monitors itself. For example, if the cluster has 10kservers, and each server has 6 buckets, each server will only need totalk with 30 different servers to maintain the status of its buckets (6buckets will have 6 penta-groups, so 6*5=30). This is a much smallernumber than if a centralized entity had to monitor all nodes and keep acluster-wide state. The use of penta-groups allows performance to scalewith bigger clusters, as nodes do not perform more work when the clustersize increases. This could pose a disadvantage that in a “dumb” mode asmall cluster could actually generate more communication than there arephysical nodes, but this disadvantage is overcome by sending just asingle heartbeat between two servers with all the buckets they share (asthe cluster grows this will change to just one bucket, but if you have asmall 5 server cluster then it will just include all the buckets in allmessages and each server will just talk with the other 4). Thepenta-groups may decide (i.e., reach consensus) using an algorithm thatresembles the Raft consensus algorithm.

Each bucket may have a group of compute nodes that can run it. Forexample, five VFS nodes can run one bucket. However, only one of thenodes in the group is the controller/leader at any given moment.Further, no two buckets share the same group, for large enough clusters.If there are only 5 or 6 nodes in the cluster, most buckets may sharebackends. In a reasonably large cluster there many distinct node groups.For example, with 26 nodes, there are more than

$64,000\left( \frac{26!}{{5!}*{\left( {26 - 5} \right)!}} \right)$possible live-node groups (i.e., penta-groups).

All nodes in a group know and agree (i.e., reach consensus) on whichnode is the actual active controller (i.e., leader) of that bucket. Anode accessing the bucket may remember (“cache”) the last node that wasthe leader for that bucket out of the (e.g., five) members of a group.If it accesses the bucket leader, the bucket leader performs therequested operation. If it accesses a node that is not the currentleader, that node indicates the leader to “redirect” the access. Ifthere is a timeout accessing the cached leader node, the contacting nodemay try a different node of the same penta-group. All the nodes in thecluster share common “configuration” of the cluster, which allows thenodes to know which server may run each bucket.

Each bucket may have a load/usage value that indicates how heavily thebucket is being used by applications running on the filesystem. Forexample, a server node with 11 lightly used buckets may receive anotherbucket of metadata to run before a server with 9 heavily used buckets,even though there will be an imbalance in the number of buckets used.Load value may be determined according to average response latencies,number of concurrently run operations, memory consumed or other metrics.

Redistribution may also occur even when a VFS node does not fail. If thesystem identifies that one node is busier than the others based on thetracked load metrics, the system can move (i.e., “fail over”) one of itsbuckets to another server that is less busy. However, before actuallyrelocating a bucket to a different host, load balancing may be achievedby diverting writes and reads. Since each write may end up on adifferent group of nodes, decided by the DFRAS, a node with a higherload may not be selected to be in a stripe to which data is beingwritten. The system may also opt to not serve reads from a highly loadednode. For example, a “degraded mode read” may be performed, wherein ablock in the highly loaded node is reconstructed from the other blocksof the same stripe. A degraded mode read is a read that is performed viathe rest of the nodes in the same stripe, and the data is reconstructedvia the failure protection. A degraded mode read may be performed whenthe read latency is too high, as the initiator of the read may assumethat that node is down. If the load is high enough to create higher readlatencies, the cluster may revert to reading that data from the othernodes and reconstructing the needed data using the degraded mode read.

Each bucket manages its own distributed erasure coding instance (i.e.,DFRAS 518) and does not need to cooperate with other buckets to performread or write operations. There are potentially thousands of concurrent,distributed erasure coding instances working concurrently, each for thedifferent bucket. This is an integral part of scaling performance, as iteffectively allows any large filesystem to be divided into independentpieces that do not need to be coordinated, thus providing highperformance regardless of the scale.

Each bucket handles all the file systems operations that fall into itsshard. For example, the directory structure, file attributes and filedata ranges will fall into a particular bucket's jurisdiction.

An operation done from any frontend starts by finding out what bucketowns that operation. Then the backend leader, and the node, for thatbucket is determined. This determination may be performed by trying thelast-known leader. If the last-known leader is not the current leader,that node may know which node is the current leader. If the last-knownleader is not part of the bucket's penta-group anymore, that backendwill let the front end know that it should go back to the configurationto find a member of the bucket's penta-group. The distribution ofoperations allows complex operations to be handled by a plurality ofservers, rather than by a single computer in a standard system.

Each 4k block in the file is handled by an object called an extent. Theextent ID is based on the inode ID and an offset (e.g., 1 MB) within thefile, and managed by the bucket. The extents are stored in the registryof each bucket. The extent ranges are protected by read-write locks.Each extent may manage the content of a contiguous 1 MB for a file, bymanaging the pointers of up to 256 4k blocks that are responsible forthat 1 MB data.

Write Operation

At block 401, an extent in a VFS backend (“BE”) receives a writerequest. The VFS frontend (“FE”) calculates the bucket that isresponsible for the extent for the 4k write (or aggregated writes). TheFE may then send the blocks to the relevant bucket over the network, andthat bucket will start handling the write. The block IDs that will beused to write these blocks are requested from the DFRAS in the FIG. 3 .If the write contains enough 4k blocks to span several contiguousextents, the first extent receives the entire write request. At block403, each extent that is part of the write locks the associated 4kblocks in order, for example from the first block of the first extent tothe last block of the last extent. Locking is done on a complete 4kblock basis, so even if the write specified new data for a portion of a4k block the complete 4k region is blocked for coherency purposes. Writelocking may be very “expensive” and is part of the reason why othersystems have limited amount of writes they can perform when they onlyhave a few metadata servers. Because the current disclosure allows anunlimited number of BE's, an unlimited number of 4k writes may beperformed concurrently.

If the requested data does not fill a complete 4k block, each 4k blockthat is touched but not completely overridden is first read. The newdata is overlaid over that block and complete 4k blocks may then bewritten to the DFRAS. For example, the user may write 5k data at anoffset of 3584. The first 512 bytes are written on the first 4k block(as the last 512 bytes of it), the second 4k block is completelyoverridden, and the third 4k block is overridden for its first 512bytes. The first and third 4k blocks will be first read, the new datawill override the correct portions of it, and then three full 4k blockswill actually be written to the DFRAS.

Each block has its EEDP (end-to-end data protection) calculated beforeit's being written to the DFRAS, and the EEDP information may also begiven to the DFRAS so it can make sure that each written block reachesthe final NVM destination unaltered with the correct EEDP. If a bit flipoccurred over the network or a logical error happened, the end node willreceive 4k block data that calculates to a different EEDP data, and thusthe DFRAS will know that it needs to resend that data again.

At block 405, once an extent acknowledges the lock, writing may begin.The write lock allows only a single write at a time over each portion ofthe extent. Two concurrent writes may occur over different ranges of theextent. If an extents is on another bucket, a remote procedure (RPC)call may be used to cause the write to execute in an address space as ifit were a local write, e.g., without explicitly coding the details forthe remote interaction.

At block 407, the journal is saved to the DFRAS. If possible, the firstblock written may be compressed to fit the journal. The journal (whichis either its own block or within the first block) is updated with thereturned block IDs. The first few bytes of the written blocks mayactually be replaced by the backpointer to the extent, which later(along with the EEDP) allows the system to make sure that the read datais intact.

At block 409, if the data to be written is not 4k aligned, or not 4kmultiple in size, the data may be padded on either (or both) ends of thebuffer to a 4k multiple. If the data is padded, existing data is readfrom the first and/or last block (same block if the write is less than4k) and the requested written data is padded with the read data, suchthat complete 4k blocks can be written. In this way small files can beunited in the inode and the extent.

At block 411, after the DFRAS are written, the extents are updated withthe block IDs, the EEDP, and also the first few bytes of data for allthe blocks. The extent may be stored in the registry, and will bedestaged to the DFRAS on the next destaging of the registry. At block413, once all the writes are done, the extent ranges are unlocked inreverse order to the locking order. Once the registry is updated, thatdata may be read.

Append Operation

A special form of a write is an append. With append, systems gets a blobof data that may be appended at the end of the current data. Doing sofrom one host with a single writer is not difficult—just find the lastoffset and perform a write operation. However, append operations mayhappen concurrently from several FEs, and the system must make sure thateach append is consistent within itself. For example, two large appendoperations must not be allowed to interleave data.

The inode knows which extent is the last extent for the file, and theextent also knows it is the last extent (only one extent may be last).Only the last extent will accept append operations. Any other extentwill reject them.

On each append operations the FE goes through the inode to find which isthe last extent. If it hit an extent that refused to perform theoperation, the FE will go through the inode again to look for the lastextent.

When an extent performs appends, it perform each append in full in theorder they were received, so when each append start executing the extentfinds the last block of data and performs the write (after locking thatblock). If the append ends after that last extent, the extent willcreate a new extent in a special mode that may execute just one appendbefore it is “open for use.” The extent may then forward the remainingpieces of the data to that extent. That extent becomes the last extentand is marked as open for use. The extent that is not last anymore, willfail all remaining append operations. The remaining append operationswill therefore go back to the FE to find who is the last extent from theinode and continue normally. If the write is large enough to spanseveral extents, the last extent will create all extents required inthat mode and will forward the correct data to be written to the createdextents. Once the all the data is written to all extents, the originalextent will mark the last extent of the append as the last and will markall extents as open for use. The original extent will then go throughall pending append operations, which will fail and be sent theoriginating FE to restart the operation and receive the correct extent.

The semantics of the operations are not affected by the order ofconcurrent appends. However, it must be ensured that no data will beinterleaved between the different writes. If the FE or the inode wouldfind the last offset and perform a standard write, there will be racesand the file will end up with inconsistent data in relation to theappend operation semantics.

Read Operation

At block 501, the extent in the VFS frontend receives the read request.It calculates and finds out what bucket is responsible for the extentthat contains the read, then finds out what backend (node) currentlyruns that bucket. Then it sends the read request over RPC to thatbucket. If a read operation spans more than one extent (more than onecontinuous 1 MB), the VFS FE may split it into several distinct readoperations that will then be aggregated back by the VFS FE. Each suchread operation may request the read to happen from a single extent. TheVFS FE then sends a read request to the node responsible to the bucketholding that extent.

At block 503, the VFS BE holding the bucket looks up an extent key inthe registry. If the extent does not exist, a buffer of zeros isreturned at block 505. At block 507, if the extent does exist, the 4kblocks in the extent are read locked and data is read from the DFRAS. Atblock 509, the registry will overlay a corresponding shadow from of thedata from VM (if one exists) over the stored data and return the actualcontent pointed to by the extent. The shadow of the extent comprisesdata changes that have not yet been committed to non-volatile memory(e.g., flash SSD). If the requested data is not 4k aligned or not 4k insize, the data is retrieved from the persistent distributed codingscheme, and then the ends may be “chopped” to meet the requested(offset, size).

At block 511, each received block is checked for the backpointer(pointing to the block ID of the extent) and the EEDP(end-to-end-data-protection). If either check fails, the extent requeststhe blocks from the distributed erasure coding of the bucket to do adegraded mode read at block 513 in which the other blocks of the stripeare read in order to reconstruct the requested block. If the extentexists, it has a list of all the blocks of a stripe that a persistentlayer stored. The reconstructed block is checked for the backpointer(pointing to the block ID of the extent) and the EEDP(end-to-end-data-protection) at block 515. At block 517, if either checkfails, an IO Error is returned. Once the correct data is confirmed atblock 511, it is returned to the requesting FE, after the first fewbytes are replaced with the original block data that was stored in theextent and override the backpointer; a new write to the distributederasure coding system (DECS) is initiated; and the extent with the newblock ID also is updated.

While the present method and/or system has been described with referenceto certain implementations, it will be understood by those skilled inthe art that various changes may be made and equivalents may besubstituted without departing from the scope of the present methodand/or system. In addition, many modifications may be made to adapt aparticular situation or material to the teachings of the presentdisclosure without departing from its scope. Therefore, it is intendedthat the present method and/or system not be limited to the particularimplementations disclosed, but that the present method and/or systemwill include all implementations falling within the scope of theappended claims.

As utilized herein the terms “circuits” and “circuitry” refer tophysical electronic components (i.e. hardware) and any software and/orfirmware (“code”) which may configure the hardware, be executed by thehardware, and or otherwise be associated with the hardware. As usedherein, for example, a particular processor and memory may comprisefirst “circuitry” when executing a first one or more lines of code andmay comprise second “circuitry” when executing a second one or morelines of code. As utilized herein, “and/or” means any one or more of theitems in the list joined by “and/or”. As an example, “x and/or y” meansany element of the three-element set {(x), (y), (x, y)}. In other words,“x and/or y” means “one or both of x and y”. As another example, “x, y,and/or z” means any element of the seven-element set {(x), (y), (z), (x,y), (x, z), (y, z), (x, y, z)}. In other words, “x, y and/or z” means“one or more of x, y and z”. As utilized herein, the term “exemplary”means serving as a non-limiting example, instance, or illustration. Asutilized herein, the terms “e.g.,” and “for example” set off lists ofone or more non-limiting examples, instances, or illustrations. Asutilized herein, circuitry is “operable” to perform a function wheneverthe circuitry comprises the necessary hardware and code (if any isnecessary) to perform the function, regardless of whether performance ofthe function is disabled or not enabled (e.g., by a user-configurablesetting, factory trim, etc.).

What is claimed is:
 1. A method for accessing storage media, the method comprising: maintaining metadata within a plurality of computing devices to map a plurality of memory blocks to a failure resilient address space, wherein: the metadata is divided into a plurality of buckets, each bucket of the plurality of buckets is associated with a unique group of two or more computing devices selected from the plurality of computing devices, the number of buckets in the plurality of buckets is determined according to the number of different pieces the metadata is divided into, and the number of different pieces the metadata is divided into is greater than the number of computing devices in the plurality of computing devices; reading data from the plurality of memory blocks; and checking data read from a particular memory block of the plurality of memory blocks for errors using a distributed erasure code based on blocks identified in an extent.
 2. The method of claim 1, wherein the failure resilient address space comprises non-volatile memory.
 3. The method of claim 1, wherein the method comprises writing data into the plurality of memory blocks.
 4. The method of claim 3, wherein writing data comprises compressing a buffer of data to be written to a first memory block of the plurality of memory blocks to provide space for a journal associated with the data written into the plurality of memory blocks.
 5. The method of claim 3, wherein writing data comprises padding a buffer of data to be written to a memory block of the plurality of memory blocks with data previously written into a portion of the memory block.
 6. The method of claim 3, wherein in coordination with writing data to a memory block of the plurality of memory blocks, the method comprises updating an extent such that the extent comprises an identification of a plurality of blocks associated with protecting the data being written to the memory block.
 7. The method of claim 1, wherein the method comprises performing a degraded data read when the particular memory block of the plurality of memory blocks is found to be in error.
 8. The method of claim 7, wherein performing a degraded data read comprises regenerating the particular memory block from one or more memory blocks other than the particular memory block of the plurality of memory blocks.
 9. A system comprising: a plurality of computing devices communicatively coupled to each other via a network, wherein: the plurality of computing devices is operable to maintain metadata that maps a plurality of memory blocks to a failure resilient address space, the metadata is divided into a plurality of buckets, each bucket of the plurality of buckets is associated with a unique group of two or more computing devices selected from the plurality of computing devices, the number of buckets in the plurality of buckets is determined according to the number of different pieces the metadata is divided into, the number of different pieces the metadata is divided into is greater than the number of computing devices in the plurality of computing devices, each of the plurality of computing devices is operable to read data from the plurality of memory blocks, and a data read from a particular memory block of the plurality of memory blocks is checked for errors using a distributed erasure code based on blocks identified in an extent.
 10. The system of claim 9, wherein the plurality of storage devices comprises non-volatile memory.
 11. The system of claim 9, wherein each of the plurality of computing devices is operable to write data into the plurality of memory blocks.
 12. The system of claim 11, wherein a buffer of data to be written to a first memory block of the plurality of memory blocks is compressed to provide space for a journal associated with the data written into the plurality of memory blocks.
 13. The system of claim 11, wherein a buffer of data to be written to a memory block of the plurality of memory blocks is padded with data previously written into a portion of the memory block.
 14. The system of claim 11, wherein in coordination with writing data to a memory block of the plurality of memory blocks, an extent is updated, and wherein the updated extent comprises an identification of a plurality of blocks associated with protecting the data being written to the memory block.
 15. The system of claim 9, wherein a degraded data read is performed when the particular memory block of the plurality of memory blocks is found to be in error.
 16. The system of claim 15, wherein the degraded data read comprises regenerating the particular memory block from one or more memory blocks other than the particular memory block of the plurality of memory blocks.
 17. A method for accessing storage media, the method comprising: maintaining metadata within a plurality of computing devices to map a plurality of memory blocks to a failure resilient address space, wherein: the metadata is divided into a plurality of buckets, each bucket of the plurality of buckets is associated with a unique group of two or more computing devices selected from the plurality of computing devices, the number of buckets in the plurality of buckets is determined according to the number of different pieces the metadata is divided into, and the number of different pieces the metadata is divided into is greater than the number of computing devices in the plurality of computing devices; writing data into the plurality of memory blocks; and writing data comprises padding a buffer of data to be written to a memory block of the plurality of memory blocks with data previously written into a portion of the memory block.
 18. The method of claim 17, wherein the failure resilient address space comprises non-volatile memory.
 19. The method of claim 17, wherein writing data comprises compressing a buffer of data to be written to a first memory block of the plurality of memory blocks to provide space for a journal associated with the data written into the plurality of memory blocks.
 20. The method of claim 17, wherein in coordination with writing data to a memory block of the plurality of memory blocks, the method comprises updating an extent such that the extent comprises an identification of a plurality of blocks associated with protecting the data being written to the memory block.
 21. The method of claim 17, wherein the method comprises reading data from the plurality of memory blocks.
 22. The method of claim 21, wherein the method comprises: checking data read from a particular memory block of the plurality of memory blocks for errors using a distributed erasure code based on blocks identified in an extent, and performing a degraded data read when the particular memory block of the plurality of memory blocks is found to be in error.
 23. The method of claim 22, wherein performing a degraded data read comprises regenerating the particular memory block from one or more memory blocks other than the particular memory block of the plurality of memory blocks.
 24. A system comprising: a plurality of computing devices communicatively coupled to each other via a network, wherein: the plurality of computing devices is operable to maintain metadata that maps a plurality of memory blocks to a failure resilient address space, the metadata is divided into a plurality of buckets, each bucket of the plurality of buckets is associated with a unique group of two or more computing devices selected from the plurality of computing devices, the number of buckets in the plurality of buckets is determined according to the number of different pieces the metadata is divided into, the number of different pieces the metadata is divided into is greater than the number of computing devices in the plurality of computing devices, each of the plurality of computing devices is operable to write data into the plurality of memory blocks, and a buffer of data to be written to a memory block of the plurality of memory blocks is padded with data previously written into a portion of the memory block.
 25. The system of claim 24, wherein the plurality of storage devices comprises non-volatile memory.
 26. The system of claim 24, wherein a buffer of data to be written to a first memory block of the plurality of memory blocks is compressed to provide space for a journal associated with the data written into the plurality of memory blocks.
 27. The system of claim 24, wherein in coordination with writing data to a memory block of the plurality of memory blocks, an extent is updated, and wherein the updated extent comprises an identification of a plurality of blocks associated with protecting the data being written to the memory block.
 28. The system of claim 24, wherein each of the plurality of computing devices is operable to read data from the plurality of memory blocks.
 29. The system of claim 28, wherein: a data read from a particular memory block of the plurality of memory blocks is checked for errors using a distributed erasure code based on blocks identified in an extent, and a degraded data read is performed when the particular memory block of the plurality of memory blocks is found to be in error.
 30. The system of claim 29, wherein the degraded data read comprises regenerating the particular memory block from one or more memory blocks other than the particular memory block of the plurality of memory blocks.
 31. A method for accessing storage media, the method comprising: maintaining metadata within a plurality of computing devices to map a plurality of memory blocks to a failure resilient address space, wherein: the metadata is divided into a plurality of buckets, each bucket of the plurality of buckets is associated with a unique group of two or more computing devices selected from the plurality of computing devices, the number of buckets in the plurality of buckets is determined according to the number of different pieces the metadata is divided into, and the number of different pieces the metadata is divided into is greater than the number of computing devices in the plurality of computing devices, writing data into the plurality of memory blocks; and updating an extent such that the extent comprises an identification of a plurality of blocks associated with protecting the data being written to the memory block.
 32. The method of claim 31, wherein the failure resilient address space comprises non-volatile memory.
 33. The method of claim 31, wherein writing data comprises compressing a buffer of data to be written to a first memory block of the plurality of memory blocks to provide space for a journal associated with the data written into the plurality of memory blocks.
 34. The method of claim 31, wherein the method comprises reading data from the plurality of memory blocks.
 35. The method of claim 34, wherein the method comprises: checking data read from a particular memory block of the plurality of memory blocks for errors using a distributed erasure code based on blocks identified in an extent, and performing a degraded data read when the particular memory block of the plurality of memory blocks is found to be in error.
 36. The method of claim 35, wherein performing a degraded data read comprises regenerating the particular memory block from one or more memory blocks other than the particular memory block of the plurality of memory blocks.
 37. A system comprising: a plurality of computing devices communicatively coupled to each other via a network, wherein: the plurality of computing devices is operable to maintain metadata that maps a plurality of memory blocks to a failure resilient address space, the metadata is divided into a plurality of buckets, each bucket of the plurality of buckets is associated with a unique group of two or more computing devices selected from the plurality of computing devices, the number of buckets in the plurality of buckets is determined according to the number of different pieces the metadata is divided into, the number of different pieces the metadata is divided into is greater than the number of computing devices in the plurality of computing devices, each of the plurality of computing devices is operable to write data into the plurality of memory blocks, and in coordination with writing data to a memory block of the plurality of memory blocks, an extent is updated, and wherein the updated extent comprises an identification of a plurality of blocks associated with protecting the data being written to the memory block.
 38. The system of claim 37, wherein the plurality of storage devices comprises non-volatile memory.
 39. The system of claim 37, wherein a buffer of data to be written to a first memory block of the plurality of memory blocks is compressed to provide space for a journal associated with the data written into the plurality of memory blocks.
 40. The system of claim 37, wherein each of the plurality of computing devices is operable to read data from the plurality of memory blocks.
 41. The system of claim 40, wherein: a data read from a particular memory block of the plurality of memory blocks is checked for errors using a distributed erasure code based on blocks identified in an extent, and a degraded data read is performed when the particular memory block of the plurality of memory blocks is found to be in error.
 42. The system of claim 41, wherein the degraded data read comprises regenerating the particular memory block from one or more memory blocks other than the particular memory block of the plurality of memory blocks. 